The systems known from the prior art involve the detection of micro-events which are characteristic of one or more different events, and the weighted accumulation over time or in space of these micro-events preferentially unveils one event, then another and so on and so forth. The detection of a micro-event generates weighted votes for each of the events, at each temporal/spatial location. In existing systems, the vote of a micro-event follows an arbitrary distribution exhibiting a different weight in the time/space domain. This therefore requires a significant quantity of memory and of operations. FIG. 1 is a basic diagram of a detection method according to the prior art. For each observation Oi, a vote value or confidence value Vi0, 11, which will serve to determine the associated event, 13 at t0, is associated with a given instant t0, 10. The generic approach to detection known from the prior art requires a memory of fairly significant size. Assuming that each of the values of the function representative of the score v is stored on a double, that is to say on 8 bytes, then, according to the generic method of the prior art, the quantity required to store v is the product of eight and the number of interesting event types (Ne), the number of detectable micro-events (M), the temporal domain of the votes, that is to say Ne*M*(2d+1), where d is the half-size of the temporal domain over which the observation is looked at. Moreover, the propagation of the information requires Ne*(2d+1) operations of addition and of reading of “doubles”, the reading of an array v[Ne][mn][dobs] where dobs corresponds to an instant of observation and of addition to an event table S[e][tn+dobs] per micro-event. For example, if Ne=30, (there are 30 different possible events), M=1000 micro-events, d=100, (equivalent of 5 seconds at 25 images per second), the memory required for the generic detector is 60 Mbytes and the number of reading operations equal to 15 000. In the case of procedures which use more micro-events, the storage memory must be able to store the equivalent of 1 Gbyte of votes, which in general is hardly compatible with a standard microcontroller. One of the known approaches for decreasing the memory and the calculations required is to compress the array v, v[Ne][M][d], for example, by the procedure described in the document entitled “best piecewise constant approximation of a function of single variable” by Hiroshi Konno et al, Operations Research Letters, volume 7, number 4, August 1988. This approach leads to a blind modification of the votes. Indeed, the votes are intermediaries between the micro-events and the segmentation. Modifying the votes without taking account of the effect on the segmentation amounts to making modifications blindly and may lead to a significant increase in the error even for weak modifications.
The document entitled “A Hough Transform-Based Voting Framework for Action Recognition” by Angela Yao et al, Conference Computer vision and Pattern Recognition, Jun. 13-18, 2010, IEEE, pages 2061-2068 describes a procedure for classifying actions or observations contained in a video sequence.
The document entitled “Simultaneous segmentation and classification for human actions in video streams using deeply optimized Hough transform” by Adrien Chan-Hong-Tong published in 2014 describes a procedure for detecting actions taking into account the temporal location of the actions.
Documents US 20130128045 and U.S. Pat. No. 5,430,810 describe procedures for line detection in images and pertain to the optimized management of the intermediate results.
The procedures described in the prior art which are known to the applicant require a fairly significant memory to process the data.
One of the objectives of the present invention is to offer a method and a system making it possible to reduce the memory size required to store the set of votes, and to reduce the number of processing operations without undermining the performance level of the detector (that is to say while remaining compatible with the effective presumed wisdom of the literature).